A number of use cases within IBM have recently driven a requirement for an efficient and scalablepersistence mechanism for RDF data. IBM made the decision to build an RDF store on top of DB2 to exploit some of the existing strengths of the relational database -- such as concurrency, compression etc. In this talk, we will cover examples of use cases for RDF, and cover specific features of the use cases that made RDF the solution of choice. We will also describe key extensions we added to the DB2 RDF solution in order to accommodate these use cases.

A number of use cases within IBM have recently driven a requirement for an efficient and scalablepersistence mechanism for RDF data. IBM made the decision to build an RDF store on top of DB2 to exploit some of the existing strengths of the relational database -- such as concurrency, compression etc. In this talk, we will cover examples of use cases for RDF, and cover specific features of the use cases that made RDF the solution of choice. We will also describe key extensions we added to the DB2 RDF solution in order to accommodate these use cases.

+

session-level: intermediate

session-level: intermediate

session-type: technology-standards-application

session-type: technology-standards-application

Revision as of 10:40, 2 June 2012

Edamam.com - Eat better with a little help from semantics and linked data with Victor Penev.

Semantic Web research intro with Lora Aroyo

In this session we will take a look at RDBMS and SQL to better understand the evolution of commonplace database systems to enable them to deal with structured data, trees and hierarchies all the way to the new IBM DB2 RDF graph support in version 10.

Full presentations

Graphs, Trees and Hierarchies in SQL - Joe Celko

SQL is intended for structured data with strong data types modeled in sets. But it is possible to effectively model trees and hierarchies in SQL Joe will show you the programming techniques. see Trees and Hierachies in SQL 2nd edition.

A number of use cases within IBM have recently driven a requirement for an efficient and scalablepersistence mechanism for RDF data. IBM made the decision to build an RDF store on top of DB2 to exploit some of the existing strengths of the relational database -- such as concurrency, compression etc. In this talk, we will cover examples of use cases for RDF, and cover specific features of the use cases that made RDF the solution of choice. We will also describe key extensions we added to the DB2 RDF solution in order to accommodate these use cases.